CN113987312A

CN113987312A - Method and device for recommending loading and unloading stop points of freight cars and storage medium

Info

Publication number: CN113987312A
Application number: CN202111290244.4A
Authority: CN
Inventors: 杨晨; 张伟; 廖泽平; 沈永新; 张河; 杨照璐; 强成仓; 石立臣
Original assignee: Shenzhen Yishi Huolala Technology Co Ltd
Current assignee: Shenzhen Yishi Huolala Technology Co Ltd
Priority date: 2021-11-02
Filing date: 2021-11-02
Publication date: 2022-01-28

Abstract

The invention provides a method, a device, computer equipment and a readable storage medium for recommending freight car loading and unloading stop points. The method reduces the scale of the point location candidate set through user information and POI addressing, and quickly and efficiently filters a batch of most appropriate point location candidate sets from a point library to select and confirm appropriate points as stop points. The method and the system are switched into a freight scene, and the point location of the loading place and the point location of the unloading place are recommended to the user, so that the communication cost of the goods handling collision surface is reduced, the influence of long-term stop of the goods van can be reduced, and the transportation efficiency and the user experience are improved.

Description

Method and device for recommending loading and unloading stop points of freight cars and storage medium

Technical Field

The present invention relates to the field of freight transportation, in particular to the field of network freight, and more particularly to a method, an apparatus, a computer device, and a computer-readable storage medium.

Background

With the continuous development of modern society, the internet technology is also continuously innovated, the internet is taken as a basis, a complete data chain is formed by the real-time data receiving and reserved data comparison on the line and a plurality of systems for auxiliary operation, the formed complete operation processing platform is called as a contract platform, and the contract platform can complete the on-line lease of vehicles. The freight industry also starts to use a network taxi booking mode for reference, a taxi and freight matching platform is developed by utilizing the internet technology, and the internet platform and the digital technology are used for prompting the whole freight internet interconnection and intercommunication under the intervention of big data, so that the high-efficiency allocation of transport capacity resources is realized.

Different from network transportation vehicles such as taxis, windmills and the like, the network transportation vehicles need to be parked at a suitable place or place for loading and unloading goods, and the positions for loading/unloading the goods need not to influence the life of citizens, the convenience of transportation and the like, for example, if the passenger transport vehicles generally get on or off the vehicles at the roadside beside the market, the side traffic is easily influenced, and even the adverse effects such as traffic jam and the like are caused when the trucks stay at the roadside for loading and unloading the goods; for example, for a community, passenger transportation generally gets on and off the door of the community, but when a truck is parked in the community, if the transportation task of a user is heavy, the driver may need to be guided to enter the community to a specific portal to load or unload goods downstairs, so that the difficulty level of the user in transporting goods is reduced.

In the prior art, the network contract platform receives the departure place and the destination of the position information, but the input departure place and the input destination do not necessarily have proper loading and unloading positions, so that the user experience is influenced.

Disclosure of Invention

In order to solve the above problems, an object of the present invention is to provide a method, an apparatus, a computer device and a computer readable storage medium for recommending loading and unloading stops of a truck, which can recommend a user to provide a site location of a loading or unloading place that is accurate and suitable, so as to reduce communication costs of the truck at the truck-cargo interface and reduce the influence of long-term stop of the truck, thereby improving transportation efficiency and experience of the user (including service users and service provider users).

Based on this, the invention provides a method for recommending loading and unloading stop points of a freight car, which comprises the following steps:

receiving a user request, the user request including user information and location information,

confirming at least one POI addressing based on the location information;

recommending at least one load/unload point candidate set based on the user information and the POI addressing recall.

Further, the location information includes a retrieval list, a history address, and/or address information input from a main key.

Further, the step of recommending at least one candidate set of load/unload points based on the user information and the POI location recall comprises:

constructing at least one recall key according to the position information and the POI address selection;

according to the recall key, multipath recall point location candidate sets;

and selecting at least one point location from the point location candidate set and recommending the point location as a loading/unloading point candidate set.

Further, the step of selecting at least one point location from the point location candidate set and recommending the point location as a loading/unloading point candidate set includes:

traversing the point location candidate set and reading the characteristics of the point locations in the point location candidate set;

calculating an ordering of the point locations in the point location candidate set based on the read features;

and selecting at least one point location recommendation as the loading/unloading point candidate set.

Further, before the step of traversing the point location candidate set and performing feature reading, the method further includes:

and acquiring all point locations in the point location candidate set based on the recall of the recall main key, and performing repeated point location de-duplication and filtering.

Further, the step of multiplexing the candidate set of recall point locations according to the recall primary key further includes:

and recalling at least one point location candidate set according to a preset recalling strategy.

Further, the recalled point location is provided with a fixed point label, and the fixed point label is used for marking whether the point location is used as a loading and unloading stop point.

The invention also provides a recommendation device for the loading and unloading stop point of the freight car, which comprises the following components:

a receiving module for receiving a user request, the user request including user information and location information,

a POI addressing module for confirming at least one POI addressing based on the location information;

and a docking point recommending module for recommending at least one loading/unloading point candidate set based on the user information and the POI addressing recall.

The invention also provides computer equipment which comprises a memory, a processor and a network interface, wherein the memory stores a computer program, and the processor executes the computer program to realize the steps of the method for recommending the loading and unloading stop points of the freight cars.

The present invention also provides a computer-readable storage medium having stored thereon a computer program which, when being executed by a processor, carries out the steps of a method for recommending a loading and unloading stop point for a freight car.

The invention provides a method for recommending loading and unloading stop points of a freight automobile, which comprises the steps of receiving a user request, confirming at least one POI (point of interest) site based on the user request, recalling a recommended loading/unloading point candidate set based on the user request and the POI site, and confirming stop points from the loading/unloading point candidate set. The method reduces the scale of the point location candidate set through user information and POI addressing, quickly and efficiently filters a batch of most appropriate point location candidate sets from a point library, and selects and confirms appropriate points from the most appropriate point location candidate sets as stop points. The method and the system are switched into a freight scene, and the point location of the loading place and the point location of the unloading place are recommended to the user, so that the communication cost of the goods handling collision surface is reduced, the influence of long-term stop of the goods van can be reduced, and the transportation efficiency and the user experience are improved.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

FIG. 1 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;

FIG. 2 is a schematic diagram of a method for recommending loading and unloading stop points for a truck according to an embodiment of the present invention;

FIG. 3 is a flowchart illustrating a hierarchical flow of a recommendation engine applied to a method for recommending a loading/unloading stop point of a truck according to an embodiment of the present invention;

FIG. 4 is a schematic diagram of a recommender of a loading/unloading stop of a truck according to an embodiment of the present invention;

FIG. 5 is a schematic block diagram of one embodiment of a computer device according to the present application.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

As shown in fig. 1, the system architecture 100 may include

terminal devices

101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the

terminal devices

101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.

The user may use the

terminal devices

101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like to operate the services and applications of the method of recommendation of freight car loading and unloading stops. The server 105 and the

terminal devices

101, 102, 103 are interconnected through the network 104 to provide a network appointment service, and the

terminal devices

101, 102, 103 may be electronic devices (such as mobile phones, computers, PDAs, etc.) used by service providers (drivers) or electronic devices (such as mobile phones, computers, PDAs, etc.) used by requesters (passengers or friends). The

terminal devices

101, 102, and 103 may further have a positioning device, where the positioning device includes, but is not limited to, a global positioning system, a beidou satellite navigation system, and the like, and is not limited herein.

The

terminal devices

101, 102, 103 may be various electronic devices having display screens and supporting web browsing, including but not limited to user devices, network devices, or devices formed by integrating user devices and network devices through a network. The user equipment includes, but is not limited to, any mobile electronic product, such as a smart phone, a tablet computer, and the like, which can perform human-computer interaction with a user through a touch panel, and the mobile electronic product may employ any operating system, such as an android operating system, an IOS operating system, and the like. The network device includes an electronic device capable of automatically performing numerical calculation and information processing according to preset or stored instructions, and the hardware includes but is not limited to a microprocessor, an Application Specific Integrated Circuit (ASIC), a programmable gate array (FPGA), a Digital Signal Processor (DSP), an embedded device, and the like. The network device comprises but is not limited to a computer, a network host, a single network server, a plurality of network server sets or a cloud formed by a plurality of servers; here, the Cloud is composed of a large number of computers or web servers based on Cloud Computing (Cloud Computing), which is a kind of distributed Computing, one virtual supercomputer consisting of a collection of loosely coupled computers. Including, but not limited to, the internet, a wide area network, a metropolitan area network, a local area network, a VPN network, a wireless Ad Hoc network (Ad Hoc network), etc. Of course, those skilled in the art should understand that the above terminal device is only an example, and other existing or future terminal devices may be applicable to the present application, and are included in the scope of the present application and are incorporated herein by reference.

The server 105 is a server of a recommendation application of a loading and unloading stop point of a freight car, and can communicate with the

terminal devices

101, 102 and 103 through the network 104, and the

terminal devices

101, 102 and 103 can be connected and communicated with each other by two parties or even multiple parties. The server 105 may be a server, a server cluster composed of several servers, or a cloud computing service center. It may also be a server providing various services, such as a background server providing support for pages displayed on the

terminal devices

101, 102, 103.

In some embodiments, the server 105 may include a processing device. The processing device may process data and/or information related to the service request to perform one or more of the functions described herein. For example, the processing device may receive an order request sent by the terminal device 101 requesting the user, and provide the user with a stop point recommending loading or unloading of the obtained goods. As another example, the processing device may send location information recommending a stop point for loading goods to the terminal device 102 service providing user so that the service provider can reach a specified location to pick up the user. Further, the processing device may include one or more sub-processing devices (e.g., a single core processing device or a multi-core processing device). By way of example only, the processing device may include a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), an Application Specific Instruction Processor (ASIP), a Graphics Processing Unit (GPU), a Physical Processing Unit (PPU), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), a programmable logic circuit (PLD), a controller, a micro-controller unit, a Reduced Instruction Set Computer (RISC), a microprocessor, or the like, or any combination thereof.

It should be noted that the method for recommending a loading/unloading stop point of a truck provided in the embodiment of the present application is generally executed by a server, and accordingly, the apparatus for recommending a loading/unloading stop point of a truck is generally disposed in a server device, and a terminal device installs a corresponding computer program or application program.

It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.

With the development of internet technology, the freight industry enters the military network booking mode, and like network booking, the freight network booking matches the relationship between vehicles and goods, and the vehicle and the goods are basically consistent in logic, and comprise a demand user side and a service providing driver user side, and the network booking driver and the vehicle are registered and audited through a network booking platform. The demand user can send an order request on the network appointment platform network through a mobile device and the like to make an appointment with a driver, and the driver receives an order to carry goods to a destination. The taxi appointment with the passenger transport network only needs to pick up passengers from a designated place and is different from the passenger transport network in destination; in the freight market, the distribution of goods also involves the time-consuming and laborious work of loading and unloading goods, which increases the difficulty of loading and unloading goods, especially when not parked in a suitable parking position.

Fig. 2 is a schematic diagram of a method for recommending a loading and unloading stop point of a freight car, according to an embodiment of the present invention, where the method includes:

201: a user request is received, the user request including user information and location information.

202: at least one POI addressing is confirmed based on the location information.

203: the recommended load/unload point candidate set is recalled based on the user information and POI addressing.

204: the load/unload docking point is determined from the load/unload point candidate set.

In an embodiment of the present invention, the target journey of the network contract passenger transport may include the following processes: inputting a departure place and a destination, ordering passengers, receiving orders by drivers and carrying goods. According to the particularity of freight transportation, in the process of inputting the departure place and the destination, the invention can recommend the proper stop position according to the input position information so as to facilitate loading or unloading goods into the truck, when carrying goods, a driver drives the vehicle to the recommended initial loading stop point to load the goods, and loads the goods to the recommended destination stop point to unload the goods in the truck.

It should be noted that the user request received in step 201 at least includes user information and location information of the requesting user terminal, and the location information includes a geographic location of the requesting point.

In some embodiments, the method of confirming addressing of at least one POI based on location information comprises: and determining one or more POI addresses associated with the position information by searching a POI database based on the geographic position of the request point, wherein the POI database is used for storing a plurality of POIs and a geographic range corresponding to each POI.

It should be noted that the POI (Point of Interest) forms a Point library, and marks a Point material library of a loading and unloading cargo. In the geographic information system, the POI may be a house, a shop, a mailbox, a bus station, etc. In an implementation mode, the point database is used for mining the obtained point locations based on the driver position positioning and trajectory reporting data in each order through an offline data mining algorithm, and the point locations are regarded as real loading and unloading point locations.

In other embodiments, the specific information of each location point in the POI-guided navigation map data includes four pieces of aspect information, name, category, address, coordinate, and other attribute information, such as longitude and latitude representations of the request point, where the longitude and latitude representations include longitude and latitude values, and the POI database stores the POIs and longitude ranges and latitude ranges corresponding to the POIs. The method for confirming at least one POI addressing based on the position information comprises the following steps: determining one or more POI addresses associated with the location information based on a relationship of the longitude and latitude values to a longitude range and a latitude range of the each POI.

Further, the location information includes location information including, but not limited to, a retrieval list, a history address, and/or address information input from a primary key. Illustratively, the location information is at least one of: the location of the indicator located on the map when the user makes a service request; a position corresponding to a certain coordinate input by the user; or a location corresponding to a name entered by the user.

Based on the POI location confirmed in step 202 and the user information acquired in step 201, at least one point location candidate set is recalled through some preset strategies such as feature reading, data processing and the like through other network models with a "recall-sort" hierarchical architecture, such as a trained deep learning neural network, and a suitable loading/unloading point candidate set is recommended to a user terminal requiring the point location candidate set through further data processing. According to the point location recommendation method and device, the loading/unloading point candidate set is recommended through the user information and POI address recall relevance, and a batch of most appropriate point location candidate sets are obtained through filtering from the point library, so that the scale of the point location candidate set can be reduced, the operating efficiency of a platform is improved, and the accuracy of loading point locations and unloading point location recommendation is improved.

In an implementable manner, the user information includes, but is not limited to, a user name and user ID information, the POI location includes, but is not limited to, POI ID and POI name information, user and POI information characteristics are read, different recall main keys are constructed, and point location candidate sets with relevance of each recall are obtained by multiple recalls from a massive point database.

In an alternative embodiment, the point location candidate set is obtained by means of a content-based recall (also called tag recall, CB () recall). Specifically, vectors may be extracted for the content of the location information and the POI addressing information, the location information and the POI addressing information may be expressed as continuous vectors, and the candidate set of POI spot locations preferred or strongly associated with the user may be recommended using similarity with the user information and/or the POI.

It should be noted that, in other embodiments, the recall method further includes, but is not limited to, collaborative filtering, FM model-based recall, a deep neural network-based method, and the like, and the deep neural network is used to generate the corresponding point location candidate set.

Further, based on the point locations of the point location candidate set recalled by the various recall strategies, appropriate point locations are pushed according to a preset rule and recommended as a loading/unloading point candidate set. If TOP N (natural number) candidate points are combined into a new list to be used as a loading/unloading point candidate set, the loading/unloading point candidate set can be directly returned to the front end for displaying or sent to the fine ranking for sorting. In other embodiments, because the refinement model is very time consuming, the recalled dots, after being coarsely ranked, will have a small amount of data sorted into the refinement.

Specifically, firstly, traversing all point locations recalled in the point location candidate set, performing duplicate removal filtering and truncation to obtain a fusion point location candidate set, and then reading the characteristics of the point locations in the point location candidate set; calculating an ordering of the point locations in the point location candidate set based on the read features; and selecting at least one point location recommendation as the loading/unloading point candidate set. In some embodiments, the model that computes the recommended load/unload point candidate set may be a ranking model, such as a LambdaMART, LambdaRank, or RankNet ranking model.

More specifically, the attribute features of the point location candidate set include, but are not limited to, the heat of candidate point locations, the location type, and the like. Heat refers to the frequency with which a user loads and unloads goods at that location. The type of the site may be a feature representing the location of the site, such as belonging to an industrial area, residential district, commercial district, office building, market street, etc. The attribute characteristics of the location information include, but are not limited to, the number of stops that the origin can recall, the degree of hotness of the origin, and the like. The degree of hotness of the origin may be the number of times that the point is used as the starting point for the user initiated order. In some embodiments, the attribute features of the origin and the first candidate pick-up point may be attribute features within a certain time period or/and a certain distance. For example, the number of times a certain stop is used to stop a load within one month, the number of times a certain stop is used to stop a load within 100m of a month, and the like.

Furthermore, a fixed point label is arranged at a point in the point library, and the fixed point label is used for marking whether the point is used as a loading and unloading stop point. And calculating the fixable point rate of the point location candidate set and the loading/unloading point candidate set according to the labels. The fixable rate of the point candidate set is a ratio of the number of orders with fixed point tags in the point candidate set to the total orders, and the fixable rate of the loading and unloading stop point is a ratio of the number of orders with fixed point tags in the loading and unloading stop point to the total orders. According to the method and the device, the fused candidate point locations are recalled through the characteristics of the stop information and the user information, the candidate set scale is reduced, and the point location sorting recommendation accuracy is improved.

In an embodiment of the invention, a loading/unloading landing is determined from the loading/unloading points, which is a location that can be used for loading and unloading goods determined in the background of a platform (e.g., a net appointment platform). It can be known that, in general, loading/unloading stop points can not be located in the middle of roads, narrow roadways and places where the terrain is complex and the trucks are inconvenient to stop. Meanwhile, the loading/unloading stop points should follow the traffic regulations of the corresponding country or region, for example, the right stop of china. Thus, for only one road and only one direction of travel, its candidate boarding point is generally to the right of the direction of travel. The real stop point is the same as the candidate stop point, and the traffic rule needs to be satisfied.

The method reduces the scale of the point location candidate set through user information and POI addressing, quickly and efficiently filters a batch of most appropriate point location candidate sets from a point library, and selects and confirms appropriate points from the most appropriate point location candidate sets as stop points. The invention is switched into a freight scene, and the point location of the loading place and the point location of the unloading place are recommended to the user, so that the communication cost of the truck collision surface is reduced, the influence of long-term stop of the truck can be reduced, and the transportation efficiency and the experience of the user (including a client and a driver) are improved.

Referring to fig. 3, a hierarchical flow chart of a recommendation engine applied in the method for recommending a loading/unloading stop point of a truck according to an embodiment of the present invention is provided. The POI location of the demand user may be determined by inputting location information in a manner of rec (Regional echo Coordinator, which is a mathematical operation symbol (point transformation from polar coordinates to rectangular coordinates) corresponding to the POI), sug (location retrieval input prompt service, also called POI hotword Suggestion retrieval, online Suggestion retrieval), drag _ map (drag positioning), and the like. The location information and the user information in the user request received in step 201 in fig. 2 include, but are not limited to, user ID, user phone, POI ID, and POI name information, a multi-way recall key is constructed according to the information, a point location candidate set with strong relevance is recalled from a point location index library, the point location candidate sets recalled in each way are fused, deduplicated, truncated, and input into a rough arrangement model for feature extraction, the fused point location candidate set is analyzed for relevance and calculated for scoring, a part or all of the one or more target POIs are ranked according to relevance probability through a fine arrangement model to generate a ranking result, and at least one load/unload point is recommended to the user terminal according to a recommendation policy.

It should be noted that the point location index library may also be used to provide other sources of information for the system for training the docking point recommendation model. For example, a point index repository may be used to provide historical orders; as another example, a point index library may be used to provide training samples, and the like. The point location index repository may be implemented in a single central server, multiple servers connected by communication links, or multiple personal devices. When the point index repository is implemented in multiple personal devices, the personal devices may generate content (e.g., referred to as "user-generated content"), for example, by uploading text, voice, images, and video to a cloud server. The point index repository may be generated by a plurality of personal devices and a cloud server. In some embodiments, the point index library may store data obtained from the

user terminals

101, 102, 103 shown in fig. 1, such as location information when the user sends a service request, or a starting place input by the user. In some embodiments, the point index repository may store information and/or instructions for execution or use by the server 105 to perform the example methods described herein. In some embodiments, the point index repository may include mass storage, removable storage, volatile read-write memory (e.g., random access memory RAM), read-only memory (ROM), the like, or any combination thereof. In some embodiments, the point index repository may be directly connected or in communication with one or more components (e.g., server 105,

user terminals

101, 102, 103) in the scene graph 100. In some embodiments, the point index repository may be part of the server 105.

It should be noted that the rough model is a trained neural network model, and the training process includes: sample construction, feature generation, feature splicing, offline training of a model and the like. The sample construction is that negative samples (indefinite point positions) are subjected to down-sampling according to the ratio of positive samples to negative samples to positive samples to negative samples, hivesql is used for calculation, a preset number of order data are taken, and some orders with abnormal fields are filtered out. Reading common characteristics of sample data, such as point location order heat characteristics associated with POI, point location order heat characteristics associated with a user, order heat characteristics around the point location (30, 20 and 10m) associated with the POI, from the sample data through a spark framework to generate a characteristic data table, splicing the sample and the characteristics according to the key of the characteristic table to obtain a final rough model training sample, training by using light-gbm, and storing the generated model as a txt file. When the model is predicted, the txt file is converted into a pmml file to deliver the project deployment. The rough arrangement model is used for circularly traversing each recall point location, reading and splicing the feature table based on key information such as POI (point of interest), inputting the features into the model to obtain a scoring result of each point location, performing descending order based on the scoring result, and taking TopN as a final recall recommendation candidate to be sent to a downstream fine arrangement model.

Fig. 4 is a schematic diagram of a device 400 for recommending loading and unloading stop points of a freight car, according to an embodiment of the present invention, the device includes:

a receiving module 401, configured to receive a user request, where the user request includes user information and location information,

a POI addressing module 402 configured to determine at least one POI addressing based on the location information;

a stop point recommending module 403, configured to recall a recommended loading/unloading point candidate set based on the user information and the POI location;

a determination module 404 for determining a loading/unloading docking point from said candidate set of loading/unloading points

The device 400 for recommending loading and unloading stop points of freight cars further comprises a display module (not shown) for displaying the software development process and the operation page of the device 400 for recommending loading and unloading stop points of freight cars.

The device 400 for recommending a loading and unloading stop of a freight car may further include an input module (not shown), the input module is connected to the display module, the input module may include a key for inputting information such as an account number, a password, and a name of a user id, the software development process operation page may be displayed on the display module of the software development device, and the display module may further display other information of the user and store the information, so that the user can view the information at any time.

The device 400 for recommending loading and unloading stop points of freight cars may further include a GPS positioning module (not shown), which includes, but is not limited to, a global positioning system, a beidou satellite navigation system, etc., and is not limited herein.

Further, the GPS positioning module is also used for presetting a target route based on the departure place, the destination and the real-time route condition of the passenger.

The device 400 for recommending loading and unloading stop points of freight cars can also comprise an interactive module (not shown), which can provide the user with a method for selecting functions, a relationship between the delivery of the guidance element and the content it guides, and a relationship between the delivery of the navigated content and the current browsing page of the user, and also provide a medium for the contact between the driver user and the passenger user.

It should be noted that the device 400 for recommending a loading/unloading stop point of a freight car in the present embodiment belongs to the same concept as that of the method embodiment, and specific implementation processes thereof are detailed in the method embodiment, and technical features in the method embodiment are correspondingly applicable in the present embodiment, and are not described herein again.

In order to solve the technical problem, an embodiment of the present application further provides a computer device. Referring to fig. 5, fig. 5 is a block diagram of a basic structure of a computer device according to the present embodiment.

The computer device 5 comprises a memory 51, a processor 52, a network interface 53 communicatively connected to each other via a system bus. It is noted that only a computer device 5 having components 51-53 is shown, but it is understood that not all of the shown components are required to be implemented, and that more or fewer components may be implemented instead. As will be understood by those skilled in the art, the computer device is a device capable of automatically performing numerical calculation and/or information processing according to a preset or stored instruction, and the hardware includes, but is not limited to, a microprocessor, an Application Specific Integrated Circuit (ASIC), a Programmable Gate Array (FPGA), a Digital Signal Processor (DSP), an embedded device, and the like.

The computer device can be a desktop computer, a notebook, a palm computer, a cloud server and other computing devices. The computer equipment can carry out man-machine interaction with a user through a keyboard, a mouse, a remote controller, a touch panel or voice control equipment and the like.

The memory 51 includes at least one type of readable storage medium including a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory 51 may be an internal storage unit of the computer device 5, such as a hard disk or a memory of the computer device 5. In other embodiments, the memory 51 may also be an external storage device of the computer device 5, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the computer device 5. Of course, the memory 51 may also comprise both an internal storage unit of the computer device 5 and an external storage device thereof. In this embodiment, the memory 51 is generally used for storing an operating system installed in the computer device 5 and various types of application software, such as program codes of a method for recommending a loading and unloading stop of a truck. Further, the memory 51 may also be used to temporarily store various types of data that have been output or are to be output.

The processor 52 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data Processing chip in some embodiments. The processor 52 is typically used to control the overall operation of the computer device 5. In this embodiment, the processor 52 is configured to execute the program code stored in the memory 51 or process data, such as program code for executing a method for recommending a loading/unloading stop of the truck.

The network interface 53 may comprise a wireless network interface or a wired network interface, and the network interface 53 is generally used for establishing communication connections between the computer device 5 and other electronic devices.

Embodiments of the present invention also provide a storage medium having stored thereon a computer program that, when executed by a processor, performs the steps of a method for recommending loading and unloading stop points for a freight car.

The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.

More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.

It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.

In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

While embodiments of the invention have been shown and described, it will be understood by those of ordinary skill in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and substitutions can be made without departing from the technical principle of the present invention, and these modifications and substitutions should also be regarded as the protection scope of the present invention.

Claims

1. A method for recommending loading and unloading stop points of a freight car is characterized by comprising the following steps:

confirming at least one POI addressing based on the location information;

recalling a recommended load/unload point candidate set based on the user information and the POI addressing;

determining a load/unload docking point from the load/unload point candidate set.

2. The method of claim 1, wherein the location information includes a search list, a history address, and/or address information input from a main key.

3. The method of claim 1, wherein said step of recalling a candidate set of recommended loading/unloading points based on said user information and said POI locations comprises:

according to the recall key, multipath recall point location candidate sets;

4. The method of claim 3 wherein said step of selecting at least one point location from said point location candidate set to recommend as a load/unload point candidate set comprises:

5. The method of recommending freight car loading and unloading stop points according to claim 4, wherein before said step of traversing said point location candidate set and performing feature reading, it further comprises:

6. The method of recommending freight car loading and unloading stop points according to claim 3, characterized in that said method further comprises:

7. The method for recommending a loading/unloading stop point of a freight car according to any one of claims 1 to 6,

the recalled point location is provided with a fixed point label which is used for marking whether the point location is used as a loading and unloading stop point or not.

8. A device for recommending loading and unloading stop points of a freight car, comprising:

a docking point recommending module for recalling a recommended loading/unloading point candidate set based on the user information and the POI addressing;

a confirmation module for determining a load/unload docking point from said candidate set of load/unload points.

9. A computer arrangement comprising a memory, a processor and a network interface, said memory storing a computer program, characterized in that said processor, when executing said computer program, carries out the steps of a method for recommending loading and unloading stop points for a freight car according to any of claims 1 to 7.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of a method for recommending loading and unloading stops for a freight car according to any of claims 1 to 7.